Pandas Profiling Report

Dataset statistics

Number of variables	39
Number of observations	10324
Missing cells	61109
Missing cells (%)	15.2%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	3.1 MiB
Average record size in memory	312.0 B

Variable types

Numeric	8
Categorical	31

Alerts

`Unit of Measure (Per Pack)` is highly correlated with `Pack Price` and 3 other fields	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 1 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Pack Price` is highly correlated with `Unit of Measure (Per Pack)`	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 5 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Unit of Measure (Per Pack)` and 4 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Unit of Measure (Per Pack)` and 4 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Adult` is highly correlated with `Product Group_ARV` and 3 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Unit of Measure (Per Pack)` and 4 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Unit of Measure (Per Pack)` is highly correlated with `Product Group_ARV` and 2 other fields	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 1 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 5 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Unit of Measure (Per Pack)` and 4 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Unit of Measure (Per Pack)` and 4 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Adult` is highly correlated with `Product Group_ARV` and 3 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Unit of Measure (Per Pack)` and 4 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Unit of Measure (Per Pack)` is highly correlated with `Product Group_HRDT`	High correlation
`Line Item Value` is highly correlated with `Line Item Insurance (USD)`	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Value`	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 5 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Unit of Measure (Per Pack)` and 4 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Adult` is highly correlated with `Product Group_ARV` and 3 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Sub Classification_Adult` and 3 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`Sub Classification_Adult` is highly correlated with `Sub Classification_HIV test` and 3 other fields	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM`	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_HRDT` is highly correlated with `Sub Classification_HIV test` and 3 other fields	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Product Group_ARV` is highly correlated with `Sub Classification_HIV test` and 3 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_From RDC` and 5 other fields	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Unit of Measure (Per Pack)` is highly correlated with `Pack Price` and 14 other fields	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 2 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Pack Price` is highly correlated with `Unit of Measure (Per Pack)` and 4 other fields	High correlation
`Unit Price` is highly correlated with `Pack Price` and 6 other fields	High correlation
`Weight (Kilograms)` is highly correlated with `Line Item Quantity`	High correlation
`Freight Cost (USD)` is highly correlated with `Unit Price`	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Managed By_Ethiopia Field Office` is highly correlated with `Managed By_Haiti Field Office`	High correlation
`Managed By_Haiti Field Office` is highly correlated with `Managed By_Ethiopia Field Office`	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Unit of Measure (Per Pack)` and 7 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Unit of Measure (Per Pack)` and 7 other fields	High correlation
`Vendor INCO Term_DDP` is highly correlated with `Fulfill Via_Direct Drop` and 3 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Unit of Measure (Per Pack)` and 9 other fields	High correlation
`Vendor INCO Term_FCA` is highly correlated with `Unit of Measure (Per Pack)`	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Unit of Measure (Per Pack)` and 7 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Vendor INCO Term_DDP` and 2 other fields	High correlation
`Shipment Mode_Truck` is highly correlated with `Vendor INCO Term_EXW` and 1 other fields	High correlation
`Product Group_ACT` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Product Group_ANTM` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Product Group_ARV` is highly correlated with `Unit of Measure (Per Pack)` and 9 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Unit of Measure (Per Pack)` and 9 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Sub Classification_Adult` is highly correlated with `Unit of Measure (Per Pack)` and 6 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Unit of Measure (Per Pack)` and 9 other fields	High correlation
`Sub Classification_HIV test - Ancillary` is highly correlated with `Unit Price`	High correlation
`Sub Classification_Malaria` is highly correlated with `Unit of Measure (Per Pack)` and 2 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Unit of Measure (Per Pack)` has 7526 (72.9%) missing values	Missing
`Line Item Quantity` has 7833 (75.9%) missing values	Missing
`Line Item Value` has 7651 (74.1%) missing values	Missing
`Pack Price` has 7591 (73.5%) missing values	Missing
`Unit Price` has 8104 (78.5%) missing values	Missing
`Weight (Kilograms)` has 7749 (75.1%) missing values	Missing
`Freight Cost (USD)` has 6980 (67.6%) missing values	Missing
`Line Item Insurance (USD)` has 7675 (74.3%) missing values	Missing

Reproduction

Analysis started	2022-05-21 12:09:12.116525
Analysis finished	2022-05-21 12:09:32.877188
Duration	20.76 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

Unit of Measure (Per Pack)
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	16
Distinct (%)	0.6%
Missing	7526
Missing (%)	72.9%
Infinite	0
Infinite (%)	0.0%
Mean	-0.387008864

Minimum	-2.545008612
Maximum	2.488270668
Zeros	0
Zeros (%)	0.0%
Negative	1695
Negative (%)	16.4%
Memory size	80.8 KiB

Quantile statistics

Minimum	-2.545008612
5-th percentile	-1.852619319
Q1	-1.246828199
median	-0.6003980502
Q3	0.7493681067
95-th percentile	1.064433964
Maximum	2.488270668
Range	5.03327928
Interquartile range (IQR)	1.996196306

Descriptive statistics

Standard deviation	1.035151287
Coefficient of variation (CV)	-2.674748264
Kurtosis	-1.20284592
Mean	-0.387008864
Median Absolute Deviation (MAD)	0.6464301492
Skewness	0.2581497963
Sum	-1082.850801
Variance	1.071538187
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=16)

Value	Count	Frequency (%)
-1.246828199	976	9.5%
0.7493681067	670	6.5%
-0.6003980502	474	4.6%
-1.852619319	222	2.2%
1.064433964	157	1.5%
0.4658112425	76	0.7%
0.2867776434	76	0.7%
0.9192583622	53	0.5%
1.214710444	39	0.4%
-2.545008612	22	0.2%
Other values (6)	33	0.3%
(Missing)	7526	72.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-2.545008612	22	0.2%
-1.852619319	222	2.2%
-1.246828199	976	9.5%
-0.6003980502	474	4.6%
-0.1484917436	1	< 0.1%
0.06854584705	1	< 0.1%
0.1616264012	3	< 0.1%
0.2867776434	76	0.7%
0.4658112425	76	0.7%
0.7493681067	670	6.5%

Value	Count	Frequency (%)
2.488270668	16	0.2%
2.126318055	5	< 0.1%
1.797300168	7	0.1%
1.214710444	39	0.4%
1.064433964	157	1.5%
0.9192583622	53	0.5%
0.7493681067	670	6.5%
0.4658112425	76	0.7%
0.2867776434	76	0.7%
0.1616264012	3	< 0.1%

Line Item Quantity
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	1885
Distinct (%)	75.7%
Missing	7833
Missing (%)	75.9%
Infinite	0
Infinite (%)	0.0%
Mean	-0.5677200651

Minimum	-7.737262175
Maximum	2.709990041
Zeros	0
Zeros (%)	0.0%
Negative	1552
Negative (%)	15.0%
Memory size	80.8 KiB

Quantile statistics

Minimum	-7.737262175
5-th percentile	-3.178408619
Q1	-1.309615138
median	-0.382846096
Q3	0.4004470332
95-th percentile	1.371545261
Maximum	2.709990041
Range	10.44725222
Interquartile range (IQR)	1.710062171

Descriptive statistics

Standard deviation	1.404417711
Coefficient of variation (CV)	-2.473785582
Kurtosis	0.9393402194
Mean	-0.5677200651
Median Absolute Deviation (MAD)	0.850234331
Skewness	-0.7968913738
Sum	-1414.190682
Variance	1.972389108
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-3.178408619	67	0.6%
-0.2344233885	62	0.6%
0.7129424932	49	0.5%
-1.792473459	27	0.3%
-1.232908996	24	0.2%
-0.613901373	22	0.2%
0.04000740584	22	0.2%
-0.4062689178	18	0.2%
-0.8762545823	17	0.2%
1.190566335	14	0.1%
Other values (1875)	2169	21.0%
(Missing)	7833	75.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-7.737262175	1	< 0.1%
-7.531038736	1	< 0.1%
-6.300657616	1	< 0.1%
-5.857198251	1	< 0.1%
-5.822849831	1	< 0.1%
-5.781509718	1	< 0.1%
-5.563995111	1	< 0.1%
-5.435743592	1	< 0.1%
-5.3746016	1	< 0.1%
-5.353263489	1	< 0.1%

Value	Count	Frequency (%)
2.709990041	1	< 0.1%
2.677742092	1	< 0.1%
2.596032464	1	< 0.1%
2.518207512	3	< 0.1%
2.517252696	1	< 0.1%
2.400936878	1	< 0.1%
2.3545038	1	< 0.1%
2.350723549	1	< 0.1%
2.25996134	1	< 0.1%
2.254836514	2	< 0.1%

Line Item Value
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2338
Distinct (%)	87.5%
Missing	7651
Missing (%)	74.1%
Infinite	0
Infinite (%)	0.0%
Mean	-0.7554450409

Minimum	-10.58742507
Maximum	2.820319876
Zeros	0
Zeros (%)	0.0%
Negative	1797
Negative (%)	17.4%
Memory size	80.8 KiB

Quantile statistics

Minimum	-10.58742507
5-th percentile	-3.34074962
Q1	-1.588360726
median	-0.6022750385
Q3	0.2477298968
95-th percentile	1.27378983
Maximum	2.820319876
Range	13.40774495
Interquartile range (IQR)	1.836090623

Descriptive statistics

Standard deviation	1.440305998
Coefficient of variation (CV)	-1.906566222
Kurtosis	2.034045603
Mean	-0.7554450409
Median Absolute Deviation (MAD)	0.9110302595
Skewness	-0.8120518696
Sum	-2019.304594
Variance	2.074481368
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-2.098960339	29	0.3%
-1.383706836	15	0.1%
-0.3540372399	10	0.1%
0.2488596517	9	0.1%
-1.074476491	8	0.1%
-0.06875557208	7	0.1%
-2.852391956	7	0.1%
-5.001060796	7	0.1%
-2.514829184	6	0.1%
-1.719698894	6	0.1%
Other values (2328)	2569	24.9%
(Missing)	7651	74.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-10.58742507	1	< 0.1%
-8.492046562	3	< 0.1%
-7.932500313	1	< 0.1%
-6.426345119	1	< 0.1%
-6.305853703	1	< 0.1%
-6.158596687	1	< 0.1%
-6.059473682	1	< 0.1%
-5.574750031	1	< 0.1%
-5.494281584	1	< 0.1%
-5.164751498	1	< 0.1%

Value	Count	Frequency (%)
2.820319876	1	< 0.1%
2.788175521	1	< 0.1%
2.706743782	1	< 0.1%
2.669362191	1	< 0.1%
2.632384823	1	< 0.1%
2.479586083	1	< 0.1%
2.46732001	1	< 0.1%
2.413157106	1	< 0.1%
2.391897128	1	< 0.1%
2.3842178	2	< 0.1%

Pack Price
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	382
Distinct (%)	14.0%
Missing	7591
Missing (%)	73.5%
Infinite	0
Infinite (%)	0.0%
Mean	-0.9302851245

Minimum	-6.634310863
Maximum	3.368069215
Zeros	0
Zeros (%)	0.0%
Negative	1686
Negative (%)	16.3%
Memory size	80.8 KiB

Quantile statistics

Minimum	-6.634310863
5-th percentile	-3.408038335
Q1	-1.636320608
median	-0.8926659564
Q3	0.2413592752
95-th percentile	0.6579009926
Maximum	3.368069215
Range	10.00238008
Interquartile range (IQR)	1.877679883

Descriptive statistics

Standard deviation	1.368560391
Coefficient of variation (CV)	-1.471119289
Kurtosis	0.4343237065
Mean	-0.9302851245
Median Absolute Deviation (MAD)	1.093605006
Skewness	-0.4844509401
Sum	-2542.469245
Variance	1.872957544
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-1.511554379	368	3.6%
0.2413592752	307	3.0%
0.3854701662	183	1.8%
-0.8672945536	84	0.8%
-1.636320608	80	0.8%
-2.35918987	76	0.7%
0.05233237855	53	0.5%
-2.198759675	47	0.5%
-2.880127967	46	0.4%
0.09290469287	44	0.4%
Other values (372)	1445	14.0%
(Missing)	7591	73.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-6.634310863	4	< 0.1%
-5.94077197	1	< 0.1%
-5.860699137	3	< 0.1%
-5.786565343	3	< 0.1%
-5.652991993	1	< 0.1%
-5.535176325	1	< 0.1%
-4.991451409	1	< 0.1%
-4.554183925	2	< 0.1%
-4.493553545	1	< 0.1%
-4.400019262	30	0.3%

Value	Count	Frequency (%)
3.368069215	1	< 0.1%
3.293074055	1	< 0.1%
3.286972715	3	< 0.1%
2.770664763	1	< 0.1%
2.699118836	1	< 0.1%
2.114935915	9	0.1%
1.973079501	39	0.4%
1.836678645	3	< 0.1%
1.832161593	3	< 0.1%
1.813207202	1	< 0.1%

Unit Price
Real number (ℝ)

HIGH CORRELATION
MISSING

Distinct	123
Distinct (%)	5.5%
Missing	8104
Missing (%)	78.5%
Infinite	0
Infinite (%)	0.0%
Mean	-2.120131245

Minimum	-6.210905782
Maximum	4.285930022
Zeros	0
Zeros (%)	0.0%
Negative	2072
Negative (%)	20.1%
Memory size	80.8 KiB

Quantile statistics

Minimum	-6.210905782
5-th percentile	-4.058674359
Q1	-2.865413854
median	-2.471765919
Q3	-1.200009787
95-th percentile	0.2920545257
Maximum	4.285930022
Range	10.4968358
Interquartile range (IQR)	1.665404067

Descriptive statistics

Standard deviation	1.38008001
Coefficient of variation (CV)	-0.6509408383
Kurtosis	1.518567037
Mean	-2.120131245
Median Absolute Deviation (MAD)	0.9536304437
Skewness	0.9128708615
Sum	-4706.691365
Variance	1.904620834
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-2.865413854	411	4.0%
-1.200009787	368	3.6%
-2.471765919	193	1.9%
-3.425396363	100	1.0%
-2.50859226	77	0.7%
-2.978801206	59	0.6%
-4.253175906	58	0.6%
-3.633233249	47	0.5%
-1.492237916	47	0.5%
1.986822286	46	0.4%
Other values (113)	814	7.9%
(Missing)	8104	78.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-6.210905782	6	0.1%
-5.286326596	4	< 0.1%
-4.814261543	14	0.1%
-4.494872204	12	0.1%
-4.253175906	58	0.6%
-4.058674359	38	0.4%
-3.895913628	43	0.4%
-3.755973	10	0.1%
-3.633233249	47	0.5%
-3.523924975	3	< 0.1%

Value	Count	Frequency (%)
4.285930022	1	< 0.1%
2.528700223	1	< 0.1%
2.421353358	2	< 0.1%
2.194043634	1	< 0.1%
2.082944401	1	< 0.1%
2.007538476	4	< 0.1%
2.001368556	3	< 0.1%
1.986822286	46	0.4%
1.921967151	23	0.2%
1.617264496	3	< 0.1%

Weight (Kilograms)
Real number (ℝ)

HIGH CORRELATION
MISSING

Distinct	1329
Distinct (%)	51.6%
Missing	7749
Missing (%)	75.1%
Infinite	0
Infinite (%)	0.0%
Mean	-1.089048401

Minimum	-8.222078619
Maximum	4.222255219
Zeros	0
Zeros (%)	0.0%
Negative	2021
Negative (%)	19.6%
Memory size	80.8 KiB

Quantile statistics

Minimum	-8.222078619
5-th percentile	-3.668356144
Q1	-1.857054632
median	-0.8685950249
Q3	-0.1557684829
95-th percentile	0.9816339957
Maximum	4.222255219
Range	12.44433384
Interquartile range (IQR)	1.701286149

Descriptive statistics

Standard deviation	1.423681812
Coefficient of variation (CV)	-1.307271385
Kurtosis	1.136628643
Mean	-1.089048401
Median Absolute Deviation (MAD)	0.842265349
Skewness	-0.6692143592
Sum	-2804.299634
Variance	2.026869901
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-0.6519831671	40	0.4%
-0.648537323	21	0.2%
-0.970809311	17	0.2%
-4.840645105	14	0.1%
-0.06123396972	13	0.1%
-2.038111328	12	0.1%
-2.379168399	11	0.1%
-0.6508332326	11	0.1%
-1.239618131	11	0.1%
-0.6515997086	10	0.1%
Other values (1319)	2415	23.4%
(Missing)	7749	75.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-8.222078619	1	< 0.1%
-8.083396682	1	< 0.1%
-7.508486545	1	< 0.1%
-7.049169343	1	< 0.1%
-6.73561109	1	< 0.1%
-6.551733538	1	< 0.1%
-6.3496504	2	< 0.1%
-5.942070361	2	< 0.1%
-5.85470693	3	< 0.1%
-5.800435945	1	< 0.1%

Value	Count	Frequency (%)
4.222255219	1	< 0.1%
3.132279581	1	< 0.1%
2.777871505	1	< 0.1%
2.487442383	1	< 0.1%
2.15329909	3	< 0.1%
1.929818763	2	< 0.1%
1.910072729	5	< 0.1%
1.903291903	1	< 0.1%
1.88992892	2	< 0.1%
1.86612376	1	< 0.1%

Freight Cost (USD)
Real number (ℝ)

HIGH CORRELATION
MISSING

Distinct	1915
Distinct (%)	57.3%
Missing	6980
Missing (%)	67.6%
Infinite	0
Infinite (%)	0.0%
Mean	-0.8849097236

Minimum	-9.377883548
Maximum	2.786167865
Zeros	0
Zeros (%)	0.0%
Negative	2447
Negative (%)	23.7%
Memory size	80.8 KiB

Quantile statistics

Minimum	-9.377883548
5-th percentile	-3.248062573
Q1	-1.674583046
median	-0.7285666091
Q3	0.05896032785
95-th percentile	1.224052545
Maximum	2.786167865
Range	12.16405141
Interquartile range (IQR)	1.733543374

Descriptive statistics

Standard deviation	1.402958769
Coefficient of variation (CV)	-1.585425871
Kurtosis	0.5976375565
Mean	-0.8849097236
Median Absolute Deviation (MAD)	0.8807960691
Skewness	-0.5073088447
Sum	-2959.138116
Variance	1.968293308
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-2.434637369	18	0.2%
-0.5381902091	18	0.2%
-2.869361638	16	0.2%
-1.193330768	16	0.2%
-0.6885823989	15	0.1%
-1.306906408	15	0.1%
-0.9631470062	14	0.1%
-0.2502118306	14	0.1%
-0.7162100987	14	0.1%
0.6141840143	13	0.1%
Other values (1905)	3191	30.9%
(Missing)	6980	67.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-9.377883548	1	< 0.1%
-6.849197684	1	< 0.1%
-6.232364958	1	< 0.1%
-6.038340316	1	< 0.1%
-5.95738177	6	0.1%
-5.950856591	1	< 0.1%
-5.699010929	1	< 0.1%
-5.594327756	1	< 0.1%
-5.467113303	1	< 0.1%
-5.375364431	1	< 0.1%

Value	Count	Frequency (%)
2.786167865	1	< 0.1%
2.595371626	1	< 0.1%
2.367413627	2	< 0.1%
2.170493703	1	< 0.1%
2.16883004	13	0.1%
2.104428922	1	< 0.1%
2.064354235	1	< 0.1%
2.063495718	1	< 0.1%
2.011877339	1	< 0.1%
1.955157398	4	< 0.1%

Line Item Insurance (USD)
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2379
Distinct (%)	89.8%
Missing	7675
Missing (%)	74.3%
Infinite	0
Infinite (%)	0.0%
Mean	-0.6593776372

Minimum	-7.990451792
Maximum	2.713955191
Zeros	0
Zeros (%)	0.0%
Negative	1718
Negative (%)	16.6%
Memory size	80.8 KiB

Quantile statistics

Minimum	-7.990451792
5-th percentile	-3.204224957
Q1	-1.525594673
median	-0.5238464586
Q3	0.3364131205
95-th percentile	1.348483084
Maximum	2.713955191
Range	10.70440698
Interquartile range (IQR)	1.862007793

Descriptive statistics

Standard deviation	1.397696899
Coefficient of variation (CV)	-2.119721416
Kurtosis	0.9656055371
Mean	-0.6593776372
Median Absolute Deviation (MAD)	0.9055838174
Skewness	-0.6768163719
Sum	-1746.691361
Variance	1.95355662
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-1.551272634	15	0.1%
-1.676889786	13	0.1%
-1.791211502	10	0.1%
-0.8892244517	8	0.1%
0.3790876814	8	0.1%
-1.973514425	6	0.1%
0.2560406659	6	0.1%
0.1858765091	6	0.1%
-1.951522152	6	0.1%
-0.6543242033	5	< 0.1%
Other values (2369)	2566	24.9%
(Missing)	7675	74.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-7.990451792	2	< 0.1%
-6.719508422	1	< 0.1%
-6.177513731	1	< 0.1%
-6.167830233	1	< 0.1%
-5.983533927	1	< 0.1%
-5.681467615	1	< 0.1%
-5.675559851	2	< 0.1%
-5.640827963	1	< 0.1%
-5.612778666	1	< 0.1%
-5.289462569	1	< 0.1%

Value	Count	Frequency (%)
2.713955191	1	< 0.1%
2.615139449	1	< 0.1%
2.442125359	1	< 0.1%
2.377378689	1	< 0.1%
2.359570735	1	< 0.1%
2.321641576	1	< 0.1%
2.311037875	1	< 0.1%
2.297220681	1	< 0.1%
2.293703743	2	< 0.1%
2.284101116	1	< 0.1%

Managed By_Ethiopia Field Office
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10323
1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10323	> 99.9%
1.0	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10323	> 99.9%
1.0	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_Haiti Field Office
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10323
1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10323	> 99.9%
1.0	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10323	> 99.9%
1.0	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_PMO - US
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	10265
0.0	59

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	10265	99.4%
0.0	59	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	10265	99.4%
0.0	59	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_South Africa Field Office
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10267
1.0	57

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10267	99.4%
1.0	57	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10267	99.4%
1.0	57	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Fulfill Via_Direct Drop
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	5404
1.0	4920

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	5404	52.3%
1.0	4920	47.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	5404	52.3%
1.0	4920	47.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Fulfill Via_From RDC
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	5404
0.0	4920

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	5404	52.3%
0.0	4920	47.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	5404	52.3%
0.0	4920	47.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_CIF
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10321
1.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10321	> 99.9%
1.0	3	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10321	> 99.9%
1.0	3	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_CIP
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10049
1.0	275

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10049	97.3%
1.0	275	2.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10049	97.3%
1.0	275	2.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DAP
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10315
1.0	9

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10315	99.9%
1.0	9	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10315	99.9%
1.0	9	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DDP
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	8881
1.0	1443

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8881	86.0%
1.0	1443	14.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8881	86.0%
1.0	1443	14.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DDU
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10309
1.0	15

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10309	99.9%
1.0	15	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10309	99.9%
1.0	15	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_EXW
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	7546
1.0	2778

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	7546	73.1%
1.0	2778	26.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7546	73.1%
1.0	2778	26.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_FCA
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	9927
1.0	397

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	9927	96.2%
1.0	397	3.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	9927	96.2%
1.0	397	3.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_N/A - From RDC
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	5404
0.0	4920

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	5404	52.3%
0.0	4920	47.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	5404	52.3%
0.0	4920	47.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Air
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	6113
0.0	4211

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	6113	59.2%
0.0	4211	40.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	6113	59.2%
0.0	4211	40.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Air Charter
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	9674
1.0	650

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	9674	93.7%
1.0	650	6.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	9674	93.7%
1.0	650	6.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Ocean
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	9953
1.0	371

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	9953	96.4%
1.0	371	3.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	9953	96.4%
1.0	371	3.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Truck
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	7494
1.0	2830

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7494	72.6%
1.0	2830	27.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7494	72.6%
1.0	2830	27.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ACT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10308
1.0	16

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10308	99.8%
1.0	16	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10308	99.8%
1.0	16	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ANTM
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10302
1.0	22

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10302	99.8%
1.0	22	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10302	99.8%
1.0	22	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ARV
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	8550
0.0	1774

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	8550	82.8%
0.0	1774	17.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	8550	82.8%
0.0	1774	17.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_HRDT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	8596
1.0	1728

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8596	83.3%
1.0	1728	16.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8596	83.3%
1.0	1728	16.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_MRDT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10316
1.0	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10316	99.9%
1.0	8	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10316	99.9%
1.0	8	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_ACT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10308
1.0	16

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10308	99.8%
1.0	16	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10308	99.8%
1.0	16	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Adult
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	6595
0.0	3729

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	6595	63.9%
0.0	3729	36.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	6595	63.9%
0.0	3729	36.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_HIV test
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	8757
1.0	1567

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8757	84.8%
1.0	1567	15.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8757	84.8%
1.0	1567	15.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_HIV test - Ancillary
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10163
1.0	161

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10163	98.4%
1.0	161	1.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10163	98.4%
1.0	161	1.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Malaria
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	10294
1.0	30

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	10294	99.7%
1.0	30	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	10294	99.7%
1.0	30	0.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Pediatric
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	8369
1.0	1955

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8369	81.1%
1.0	1955	18.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8369	81.1%
1.0	1955	18.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

First Line Designation_No
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0.0	7030
1.0	3294

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7030	68.1%
1.0	3294	31.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7030	68.1%
1.0	3294	31.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

First Line Designation_Yes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1.0	7030
0.0	3294

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	7030	68.1%
0.0	3294	31.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	7030	68.1%
0.0	3294	31.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Unit of Measure (Per Pack)	Line Item Quantity	Line Item Value	Pack Price	Unit Price	Weight (Kilograms)	Freight Cost (USD)	Line Item Insurance (USD)	Managed By_PMO - US	Fulfill Via_Direct Drop	Vendor INCO Term_CIP	Vendor INCO Term_DDU	Vendor INCO Term_EXW	Vendor INCO Term_FCA	Shipment Mode_Air	Product Group_ARV	Product Group_HRDT	Sub Classification_Adult	Sub Classification_HIV test	Sub Classification_Pediatric	First Line Designation_No	First Line Designation_Yes
0	NaN	NaN	NaN	-1.865678	-2.217704	NaN	NaN	NaN	1.0	1.0	0.0	0.0	1.0	0.0	1.0	0.0	1.0	0.0	1.0	0.0	0.0	1.0
1	0.749368	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0
2	-1.246828	NaN	NaN	0.241359	-2.865414	NaN	NaN	NaN	1.0	1.0	0.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	1.0	0.0	0.0	1.0
3	NaN	-1.080566	NaN	NaN	NaN	NaN	-1.427223	NaN	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0
4	NaN	-0.710747	NaN	NaN	NaN	-1.32578	0.672544	NaN	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0
5	0.749368	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0
6	-1.852619	NaN	NaN	-1.472563	NaN	NaN	NaN	NaN	1.0	1.0	0.0	1.0	0.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0
7	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0
8	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.0	1.0	0.0	0.0	1.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	1.0	0.0
9	-0.600398	NaN	NaN	-0.867295	NaN	NaN	NaN	NaN	1.0	1.0	1.0	0.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0

Last rows

	Unit of Measure (Per Pack)	Line Item Quantity	Line Item Value	Pack Price	Unit Price	Weight (Kilograms)	Freight Cost (USD)	Line Item Insurance (USD)	Managed By_PMO - US	Fulfill Via_From RDC	Vendor INCO Term_N/A - From RDC	Shipment Mode_Air	Shipment Mode_Air Charter	Shipment Mode_Truck	Product Group_ARV	Sub Classification_Adult	Sub Classification_Pediatric	First Line Designation_No	First Line Designation_Yes
10314	NaN	NaN	NaN	NaN	NaN	-1.819625	-1.222445	NaN	1.0	1.0	1.0	0.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0
10315	-0.600398	0.255115	1.200701	NaN	NaN	-0.135016	-0.181529	0.801773	1.0	1.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0
10316	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.0	1.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0
10317	NaN	NaN	NaN	NaN	NaN	-1.876439	0.725691	NaN	1.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0
10318	NaN	1.540917	0.520780	NaN	NaN	0.546682	0.692066	0.244420	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0
10319	NaN	1.309109	0.246951	NaN	NaN	0.546682	0.692066	-0.055598	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0
10320	NaN	-2.681951	NaN	NaN	NaN	-4.366331	-1.797627	NaN	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0
10321	NaN	2.517253	2.669362	NaN	NaN	1.540116	1.160876	2.321642	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0
10322	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0
10323	NaN	-0.782459	NaN	NaN	NaN	-0.343383	NaN	NaN	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script